PAM Engineer AI, Machine Learning & Automation
Overview
As a PAM Engineer AI, you will own the end-to-end design and deployment of AI-enabled, LLM-based applications that drive automation and agentic systems. You will architect agent orchestration frameworks, implement RAG-based grounding, and manage tool invocation and state across multi-agent environments. Working within a hybrid model in New York City, you will collaborate with cross-functional teams to ship production-grade solutions. This role focuses on pushing the boundaries of autonomous decision-making and policy-aware execution.
What You'll Do7
- 1Build agent orchestration architectures that support task decomposition and multi-agent coordination using Python and LangChain.
- 2Design LLM interaction layers with prompt engineering and grounding strategies like RAG to ensure reliable responses.
- 3Implement tool and function invocation mechanisms, managing state and memory across agent sessions.
- 4Develop policy-aware execution flows that align with security and compliance requirements.
- 5Scale AI applications on AWS or Azure with containerization using Docker and Kubernetes.
- 6Debug and optimize agent performance, measuring latency, accuracy, and cost.
- 7Ship automation solutions that reduce manual intervention in enterprise workflows.
Requirements8
- 13+ years of experience in AI or ML engineering, with a focus on LLM-based systems.
- 22+ years of hands-on work with Python and relevant frameworks like LangChain or LlamaIndex.
- 31+ years using RAG for grounded generation.
- 42+ years building applications on AWS or Azure.
- 5Familiarity with Docker and Kubernetes for deployment.
- 61+ years experience with agent orchestration or multi-agent systems.
- 7Knowledge of RESTful APIs and service integration.
- 8Bachelor's degree in Computer Science, Engineering, or a related field.
Salary Insight
$83 - $104k per year
Location
Required Skills
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